SPdel notebook example file¶
In [1]:
import SPdel
import os
In [2]:
fasta = './data/Megaleporinus/Megaleporinus_COI.fasta'
tree = './data/Megaleporinus/Megaleporinus_tree.nwk'
basepath=os.path.dirname(fasta)
Inputs=SPdel.reading_data(fasta,tree)
############################################################################ SPdel v2.0 - Species delimitation and statistics for DNA Barcoding data sets ############################################################################ Sequences are aligned (same size) Fasta file with 116 sequences and 600 base pairs
Analyzing data using nominal delimitation¶
In [3]:
nominal=SPdel.run_nominal(basepath,Inputs)
##################### Nominal MOTUs ##################### #####LS_brn##### LS_brn_L930, LS_brn_L931, LS_brn_L932 #####LS_con##### LS_con_L210, LS_con_L211, LS_con_L286, LS_con_L291, LS_con_L292, LS_con_L820 #####LS_elo##### LS_elo_L1041, LS_elo_L1046, LS_elo_L1047, LS_elo_L287, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L309 #####LS_gar##### LS_gar_L293, LS_gar_L294, LS_gar_L295, LS_gar_L296, LS_gar_L298 #####LS_mac##### LS_mac_B061, LS_mac_B082, LS_mac_B086, LS_mac_B087, LS_mac_B088, LS_mac_B089, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L212, LS_mac_L225, LS_mac_L290, LS_mac_L890, LS_mac_L891 #####LS_muy##### LS_muy_L907, LS_muy_L913, LS_muy_L914, LS_muy_L915 #####LS_obt##### LS_obt_B031, LS_obt_B070, LS_obt_B071, LS_obt_B074, LS_obt_B075, LS_obt_B077, LS_obt_B090, LS_obt_B100, LS_obt_B101, LS_obt_B102, LS_obt_B103, LS_obt_L004, LS_obt_L007, LS_obt_L008, LS_obt_L009, LS_obt_L013, LS_obt_L016, LS_obt_L084, LS_obt_L253, LS_obt_L266, LS_obt_L267, LS_obt_L268, LS_obt_L269, LS_obt_L282, LS_obt_L283, LS_obt_L314, LS_obt_L315, LS_obt_L316, LS_obt_L320, LS_obt_L547, LS_obt_L548 #####LS_piv##### LS_piv_B060, LS_piv_B076, LS_piv_B078, LS_piv_B093, LS_piv_B094, LS_piv_B095, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099, LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144, LS_piv_L002, LS_piv_L003, LS_piv_L005, LS_piv_L006, LS_piv_L010, LS_piv_L011, LS_piv_L014, LS_piv_L284, LS_piv_L371 #####LS_rei##### LS_rei_B072, LS_rei_B073, LS_rei_L338, LS_rei_L339, LS_rei_L341, LS_rei_L342, LS_rei_L343, LS_rei_L353, LS_rei_L355, LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779 #####LS_tri##### LS_tri_L179, LS_tri_L180, LS_tri_L182, LS_tri_L519, LS_tri_L618, LS_tri_L621, LS_tri_L690, LS_tri_L955 Using k2p distance
In [4]:
nominal.print_summary()
Out[4]:
| Mean | Max | NN | DtoNN | |
|---|---|---|---|---|
| LS_brn | 0.000000 | 0.00000 | LS_obt | 6.77516 |
| LS_con | 2.127067 | 3.98825 | LS_obt | 5.60360 |
| LS_elo | 0.037100 | 0.16695 | LS_obt | 2.73593 |
| LS_gar | 0.000000 | 0.00000 | LS_obt | 7.68126 |
| LS_mac | 0.903538 | 1.85854 | LS_tri | 4.51779 |
| LS_muy | 7.655915 | 15.31183 | LS_tri | 7.47916 |
| LS_obt | 1.937511 | 6.71724 | LS_elo | 2.73593 |
| LS_piv | 0.266286 | 1.00758 | LS_obt | 2.90372 |
| LS_rei | 0.316828 | 0.70177 | LS_con | 6.14484 |
| LS_tri | 3.392014 | 6.33176 | LS_mac | 4.51779 |
Analyzing data using PTP species delimitation¶
In [5]:
PTP=SPdel.run_PTP(basepath,Inputs)
Speciation rate: 43.602 Coalesecnt rate: 1666.347 Null logl: 959.787 MAX logl: 1249.664 P-value: 0.000 Kolmogorov-Smirnov test for model fitting: Speciation: Dtest = 0.539 p-value >= 0.1 excellent model fitting Coalescent: Dtest = 2.220 p-value < 0.01 poor model fitting Number of species: 18 ##################### PTP MOTUs ##################### #####MOTU_01##### LS_muy_L913, LS_muy_L915, LS_muy_L914 #####MOTU_02##### LS_muy_L907 #####MOTU_03##### LS_brn_L930, LS_brn_L931, LS_brn_L932 #####MOTU_04##### LS_gar_L293, LS_gar_L298, LS_gar_L294, LS_gar_L296, LS_gar_L295 #####MOTU_05##### LS_tri_L179, LS_tri_L180, LS_tri_L182 #####MOTU_06##### LS_con_L286, LS_con_L820, LS_con_L291, LS_con_L292 #####MOTU_07##### LS_con_L210, LS_con_L211 #####MOTU_08##### LS_tri_L519, LS_tri_L690, LS_tri_L618, LS_tri_L955, LS_tri_L621 #####MOTU_09##### LS_obt_B074, LS_obt_L016, LS_obt_B077, LS_obt_B075, LS_obt_L009, LS_obt_L548, LS_obt_L004, LS_obt_L013, LS_obt_L283, LS_obt_L282, LS_obt_L547, LS_obt_L007, LS_obt_L008, LS_obt_B100, LS_obt_B103, LS_obt_B101, LS_obt_B102 #####MOTU_10##### LS_elo_L1041, LS_elo_L287, LS_elo_L309, LS_elo_L1046, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L1047 #####MOTU_11##### LS_obt_B031, LS_obt_B090, LS_obt_B070, LS_obt_L268, LS_obt_L266, LS_obt_L316, LS_obt_B071, LS_obt_L267, LS_obt_L269, LS_obt_L253, LS_obt_L314, LS_obt_L315, LS_obt_L320 #####MOTU_12##### LS_obt_L084 #####MOTU_13##### LS_mac_B061, LS_mac_B086, LS_mac_B089, LS_mac_B087, LS_mac_B088 #####MOTU_14##### LS_mac_B082, LS_mac_L890, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L225, LS_mac_L212, LS_mac_L891, LS_mac_L290 #####MOTU_15##### LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779 #####MOTU_16##### LS_rei_B072, LS_rei_L342, LS_rei_B073, LS_rei_L341, LS_rei_L338, LS_rei_L355, LS_rei_L339, LS_rei_L343, LS_rei_L353 #####MOTU_17##### LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144 #####MOTU_18##### LS_piv_B060, LS_piv_B095, LS_piv_B093, LS_piv_L002, LS_piv_L003, LS_piv_L011, LS_piv_L010, LS_piv_B076, LS_piv_B094, LS_piv_L284, LS_piv_L371, LS_piv_B078, LS_piv_L005, LS_piv_L006, LS_piv_L014, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099 Using k2p distance
In [6]:
PTP.print_summary()
Out[6]:
| Mean | Max | NN | DtoNN | |
|---|---|---|---|---|
| MOTU_01 | 0.000000 | 0.00000 | MOTU_03 | 11.60407 |
| MOTU_02 | NaN | NaN | MOTU_08 | 7.47916 |
| MOTU_03 | 0.000000 | 0.00000 | MOTU_09 | 6.77516 |
| MOTU_04 | 0.000000 | 0.00000 | MOTU_09 | 7.68126 |
| MOTU_05 | 0.000000 | 0.00000 | MOTU_08 | 6.33176 |
| MOTU_06 | 0.000000 | 0.00000 | MOTU_07 | 3.98825 |
| MOTU_07 | 0.000000 | 0.00000 | MOTU_06 | 3.98825 |
| MOTU_08 | 0.000000 | 0.00000 | MOTU_14 | 4.51779 |
| MOTU_09 | 0.143081 | 0.50167 | MOTU_11 | 2.84291 |
| MOTU_10 | 0.037100 | 0.16695 | MOTU_11 | 2.73593 |
| MOTU_11 | 0.000000 | 0.00000 | MOTU_10 | 2.73593 |
| MOTU_12 | NaN | NaN | MOTU_17 | 2.90372 |
| MOTU_13 | 0.136404 | 0.34101 | MOTU_14 | 1.55005 |
| MOTU_14 | 0.000000 | 0.00000 | MOTU_13 | 1.55005 |
| MOTU_15 | 0.000000 | 0.00000 | MOTU_16 | 0.67115 |
| MOTU_16 | 0.000000 | 0.00000 | MOTU_15 | 0.67115 |
| MOTU_17 | 0.083475 | 0.16695 | MOTU_18 | 0.67024 |
| MOTU_18 | 0.058574 | 0.16772 | MOTU_17 | 0.67024 |
Analyzing data using bPTP species delimitation¶
In [7]:
bPTP=SPdel.run_bPTP(basepath,Inputs)
Estimated number of species is between 17 and 21 Mean: 18.56 bPTP finished running with the following parameters: MCMC iterations:................10000 MCMC sampling interval:.........100 MCMC burn-in:...................0.10 MCMC seed:......................1234 ##################### bPTP MOTUs ##################### #####MOTU_01##### LS_muy_L913, LS_muy_L915, LS_muy_L914 #####MOTU_02##### LS_muy_L907 #####MOTU_03##### LS_brn_L930, LS_brn_L931, LS_brn_L932 #####MOTU_04##### LS_gar_L293, LS_gar_L298, LS_gar_L294, LS_gar_L296, LS_gar_L295 #####MOTU_05##### LS_tri_L179, LS_tri_L180, LS_tri_L182 #####MOTU_06##### LS_con_L286, LS_con_L820, LS_con_L291, LS_con_L292 #####MOTU_07##### LS_con_L210, LS_con_L211 #####MOTU_08##### LS_tri_L519, LS_tri_L690, LS_tri_L618, LS_tri_L955, LS_tri_L621 #####MOTU_09##### LS_obt_B074, LS_obt_L016, LS_obt_B077, LS_obt_B075, LS_obt_L009, LS_obt_L548, LS_obt_L004, LS_obt_L013, LS_obt_L283, LS_obt_L282, LS_obt_L547, LS_obt_L007, LS_obt_L008, LS_obt_B100, LS_obt_B103, LS_obt_B101, LS_obt_B102 #####MOTU_10##### LS_elo_L1041, LS_elo_L287, LS_elo_L309, LS_elo_L1046, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L1047 #####MOTU_11##### LS_obt_B031, LS_obt_B090, LS_obt_B070, LS_obt_L268, LS_obt_L266, LS_obt_L316, LS_obt_B071, LS_obt_L267, LS_obt_L269, LS_obt_L253, LS_obt_L314, LS_obt_L315, LS_obt_L320 #####MOTU_12##### LS_obt_L084 #####MOTU_13##### LS_mac_B061, LS_mac_B086, LS_mac_B089, LS_mac_B087, LS_mac_B088 #####MOTU_14##### LS_mac_B082, LS_mac_L890, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L225, LS_mac_L212, LS_mac_L891, LS_mac_L290 #####MOTU_15##### LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779 #####MOTU_16##### LS_rei_B072, LS_rei_L342, LS_rei_B073, LS_rei_L341, LS_rei_L338, LS_rei_L355, LS_rei_L339, LS_rei_L343, LS_rei_L353 #####MOTU_17##### LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144 #####MOTU_18##### LS_piv_B060, LS_piv_B095, LS_piv_B093, LS_piv_L002, LS_piv_L003, LS_piv_L011, LS_piv_L010, LS_piv_B076, LS_piv_B094, LS_piv_L284, LS_piv_L371, LS_piv_B078, LS_piv_L005, LS_piv_L006, LS_piv_L014, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099 Using k2p distance
<Figure size 640x480 with 0 Axes>
In [8]:
bPTP.print_summary()
Out[8]:
| Mean | Max | NN | DtoNN | |
|---|---|---|---|---|
| MOTU_01 | 0.000000 | 0.00000 | MOTU_03 | 11.60407 |
| MOTU_02 | NaN | NaN | MOTU_08 | 7.47916 |
| MOTU_03 | 0.000000 | 0.00000 | MOTU_09 | 6.77516 |
| MOTU_04 | 0.000000 | 0.00000 | MOTU_09 | 7.68126 |
| MOTU_05 | 0.000000 | 0.00000 | MOTU_08 | 6.33176 |
| MOTU_06 | 0.000000 | 0.00000 | MOTU_07 | 3.98825 |
| MOTU_07 | 0.000000 | 0.00000 | MOTU_06 | 3.98825 |
| MOTU_08 | 0.000000 | 0.00000 | MOTU_14 | 4.51779 |
| MOTU_09 | 0.143081 | 0.50167 | MOTU_11 | 2.84291 |
| MOTU_10 | 0.037100 | 0.16695 | MOTU_11 | 2.73593 |
| MOTU_11 | 0.000000 | 0.00000 | MOTU_10 | 2.73593 |
| MOTU_12 | NaN | NaN | MOTU_17 | 2.90372 |
| MOTU_13 | 0.136404 | 0.34101 | MOTU_14 | 1.55005 |
| MOTU_14 | 0.000000 | 0.00000 | MOTU_13 | 1.55005 |
| MOTU_15 | 0.000000 | 0.00000 | MOTU_16 | 0.67115 |
| MOTU_16 | 0.000000 | 0.00000 | MOTU_15 | 0.67115 |
| MOTU_17 | 0.083475 | 0.16695 | MOTU_18 | 0.67024 |
| MOTU_18 | 0.058574 | 0.16772 | MOTU_17 | 0.67024 |
Analyzing data using mPTP species delimitation¶
Another method included in SPdel is the Multi-rate Poisson tree processes - mPTP (Kapli, et al. 2016). Of course, you can obtain all same metrics and figures as previous methods
In [9]:
mPTP=SPdel.run_mPTP(basepath,Inputs)
##################### mPTP MOTUs ##################### #####MOTU_01##### LS_con_L286, LS_con_L820, LS_con_L291, LS_con_L292 #####MOTU_02##### LS_con_L210, LS_con_L211 #####MOTU_03##### LS_brn_L930, LS_brn_L931, LS_brn_L932 #####MOTU_04##### LS_elo_L1041, LS_elo_L287, LS_elo_L309, LS_elo_L1046, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L1047 #####MOTU_05##### LS_obt_B031, LS_obt_B090, LS_obt_B070, LS_obt_L268, LS_obt_L266, LS_obt_L316, LS_obt_B071, LS_obt_L267, LS_obt_L269, LS_obt_L253, LS_obt_L314, LS_obt_L315, LS_obt_L320 #####MOTU_06##### LS_obt_B074, LS_obt_L016, LS_obt_B077, LS_obt_B075, LS_obt_L009, LS_obt_L548, LS_obt_L004, LS_obt_L013, LS_obt_L283, LS_obt_L282, LS_obt_L547, LS_obt_L007, LS_obt_L008, LS_obt_B100, LS_obt_B103, LS_obt_B101, LS_obt_B102 #####MOTU_07##### LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144, LS_piv_B060, LS_piv_B095, LS_piv_B093, LS_piv_L002, LS_piv_L003, LS_piv_L011, LS_piv_L010, LS_piv_B076, LS_piv_B094, LS_piv_L284, LS_piv_L371, LS_piv_B078, LS_piv_L005, LS_piv_L006, LS_piv_L014, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099 #####MOTU_08##### LS_obt_L084 #####MOTU_09##### LS_gar_L293, LS_gar_L298, LS_gar_L294, LS_gar_L296, LS_gar_L295 #####MOTU_10##### LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779 #####MOTU_11##### LS_rei_B072, LS_rei_L342, LS_rei_B073, LS_rei_L341, LS_rei_L338, LS_rei_L355, LS_rei_L339, LS_rei_L343, LS_rei_L353 #####MOTU_12##### LS_muy_L913, LS_muy_L915, LS_muy_L914 #####MOTU_13##### LS_muy_L907 #####MOTU_14##### LS_tri_L179, LS_tri_L180, LS_tri_L182 #####MOTU_15##### LS_mac_B061, LS_mac_B086, LS_mac_B089, LS_mac_B087, LS_mac_B088 #####MOTU_16##### LS_mac_B082, LS_mac_L890, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L225, LS_mac_L212, LS_mac_L891, LS_mac_L290 #####MOTU_17##### LS_tri_L519, LS_tri_L690, LS_tri_L618, LS_tri_L955, LS_tri_L621 Using k2p distance
In [10]:
mPTP.print_summary()
Out[10]:
| Mean | Max | NN | DtoNN | |
|---|---|---|---|---|
| MOTU_01 | 0.000000 | 0.00000 | MOTU_02 | 3.98825 |
| MOTU_02 | 0.000000 | 0.00000 | MOTU_01 | 3.98825 |
| MOTU_03 | 0.000000 | 0.00000 | MOTU_06 | 6.77516 |
| MOTU_04 | 0.037100 | 0.16695 | MOTU_05 | 2.73593 |
| MOTU_05 | 0.000000 | 0.00000 | MOTU_04 | 2.73593 |
| MOTU_06 | 0.143081 | 0.50167 | MOTU_05 | 2.84291 |
| MOTU_07 | 0.266286 | 1.00758 | MOTU_08 | 2.90372 |
| MOTU_08 | NaN | NaN | MOTU_07 | 2.90372 |
| MOTU_09 | 0.000000 | 0.00000 | MOTU_06 | 7.68126 |
| MOTU_10 | 0.000000 | 0.00000 | MOTU_11 | 0.67115 |
| MOTU_11 | 0.000000 | 0.00000 | MOTU_10 | 0.67115 |
| MOTU_12 | 0.000000 | 0.00000 | MOTU_03 | 11.60407 |
| MOTU_13 | NaN | NaN | MOTU_17 | 7.47916 |
| MOTU_14 | 0.000000 | 0.00000 | MOTU_17 | 6.33176 |
| MOTU_15 | 0.136404 | 0.34101 | MOTU_16 | 1.55005 |
| MOTU_16 | 0.000000 | 0.00000 | MOTU_15 | 1.55005 |
| MOTU_17 | 0.000000 | 0.00000 | MOTU_16 | 4.51779 |
Analyzing data using GMYC species delimitation¶
In [11]:
GMYC=SPdel.run_GMYC(basepath,Inputs)
Highest llh:1004.3909296154683 Num spe:18 Null llh:968.4341056152681 P-value:2.220446049250313e-16 Final number of estimated species by GMYC: 18 ##################### GMYC MOTUs ##################### #####MOTU_01##### LS_obt_B074, LS_obt_L016, LS_obt_B077, LS_obt_B075, LS_obt_L009, LS_obt_L548, LS_obt_L004, LS_obt_L013, LS_obt_L283, LS_obt_L282, LS_obt_L547, LS_obt_L007, LS_obt_L008, LS_obt_B100, LS_obt_B103, LS_obt_B101, LS_obt_B102 #####MOTU_02##### LS_piv_B060, LS_piv_B095, LS_piv_B093, LS_piv_L002, LS_piv_L003, LS_piv_L011, LS_piv_L010, LS_piv_B076, LS_piv_B094, LS_piv_L284, LS_piv_L371, LS_piv_B078, LS_piv_L005, LS_piv_L006, LS_piv_L014, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099 #####MOTU_03##### LS_mac_B082, LS_mac_L890, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L225, LS_mac_L212, LS_mac_L891, LS_mac_L290 #####MOTU_04##### LS_obt_B031, LS_obt_B090, LS_obt_B070, LS_obt_L268, LS_obt_L266, LS_obt_L316, LS_obt_B071, LS_obt_L267, LS_obt_L269, LS_obt_L253, LS_obt_L314, LS_obt_L315, LS_obt_L320 #####MOTU_05##### LS_mac_B061, LS_mac_B086, LS_mac_B089, LS_mac_B087, LS_mac_B088 #####MOTU_06##### LS_elo_L1041, LS_elo_L287, LS_elo_L309, LS_elo_L1046, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L1047 #####MOTU_07##### LS_rei_B072, LS_rei_L342, LS_rei_B073, LS_rei_L341, LS_rei_L338, LS_rei_L355, LS_rei_L339, LS_rei_L343, LS_rei_L353 #####MOTU_08##### LS_tri_L519, LS_tri_L690, LS_tri_L618, LS_tri_L955, LS_tri_L621 #####MOTU_09##### LS_gar_L293, LS_gar_L298, LS_gar_L294, LS_gar_L296, LS_gar_L295 #####MOTU_10##### LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144 #####MOTU_11##### LS_con_L286, LS_con_L820, LS_con_L291, LS_con_L292 #####MOTU_12##### LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779 #####MOTU_13##### LS_tri_L179, LS_tri_L180, LS_tri_L182 #####MOTU_14##### LS_muy_L913, LS_muy_L915, LS_muy_L914 #####MOTU_15##### LS_brn_L930, LS_brn_L931, LS_brn_L932 #####MOTU_16##### LS_con_L210, LS_con_L211 #####MOTU_17##### LS_obt_L084 #####MOTU_18##### LS_muy_L907 Using k2p distance
In [12]:
GMYC.print_summary()
Out[12]:
| Mean | Max | NN | DtoNN | |
|---|---|---|---|---|
| MOTU_01 | 0.143081 | 0.50167 | MOTU_04 | 2.84291 |
| MOTU_02 | 0.058574 | 0.16772 | MOTU_10 | 0.67024 |
| MOTU_03 | 0.000000 | 0.00000 | MOTU_05 | 1.55005 |
| MOTU_04 | 0.000000 | 0.00000 | MOTU_06 | 2.73593 |
| MOTU_05 | 0.136404 | 0.34101 | MOTU_03 | 1.55005 |
| MOTU_06 | 0.037100 | 0.16695 | MOTU_04 | 2.73593 |
| MOTU_07 | 0.000000 | 0.00000 | MOTU_12 | 0.67115 |
| MOTU_08 | 0.000000 | 0.00000 | MOTU_03 | 4.51779 |
| MOTU_09 | 0.000000 | 0.00000 | MOTU_01 | 7.68126 |
| MOTU_10 | 0.083475 | 0.16695 | MOTU_02 | 0.67024 |
| MOTU_11 | 0.000000 | 0.00000 | MOTU_16 | 3.98825 |
| MOTU_12 | 0.000000 | 0.00000 | MOTU_07 | 0.67115 |
| MOTU_13 | 0.000000 | 0.00000 | MOTU_08 | 6.33176 |
| MOTU_14 | 0.000000 | 0.00000 | MOTU_15 | 11.60407 |
| MOTU_15 | 0.000000 | 0.00000 | MOTU_01 | 6.77516 |
| MOTU_16 | 0.000000 | 0.00000 | MOTU_11 | 3.98825 |
| MOTU_17 | NaN | NaN | MOTU_10 | 2.90372 |
| MOTU_18 | NaN | NaN | MOTU_08 | 7.47916 |
Analyzing data using ABGD species delimitation¶
In [13]:
ABGD=SPdel.run_ABGD(basepath,Inputs)
groups P ABGD_1 27 0.001000 ABGD_2 27 0.001670 ABGD_3 19 0.002780 ABGD_4 18 0.004640 ABGD_5 16 0.007740 ABGD_6 16 0.012900 ABGD_7 15 0.021544 ##################### ABGD MOTUs ##################### #####MOTU_01##### LS_brn_L930, LS_brn_L931, LS_brn_L932 #####MOTU_02##### LS_con_L210, LS_con_L211 #####MOTU_03##### LS_con_L286, LS_con_L291, LS_con_L292, LS_con_L820 #####MOTU_04##### LS_elo_L1041, LS_elo_L1046, LS_elo_L1047, LS_elo_L287, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L309 #####MOTU_05##### LS_gar_L293, LS_gar_L294, LS_gar_L295, LS_gar_L296, LS_gar_L298 #####MOTU_06##### LS_mac_B061, LS_mac_B086, LS_mac_B087, LS_mac_B088, LS_mac_B089 #####MOTU_07##### LS_muy_L907 #####MOTU_08##### LS_muy_L913, LS_muy_L914, LS_muy_L915 #####MOTU_09##### LS_obt_B031, LS_obt_B070, LS_obt_B071, LS_obt_B090, LS_obt_L253, LS_obt_L266, LS_obt_L267, LS_obt_L268, LS_obt_L269, LS_obt_L314, LS_obt_L315, LS_obt_L316, LS_obt_L320 #####MOTU_10##### LS_obt_B074, LS_obt_B075, LS_obt_B077, LS_obt_B100, LS_obt_B101, LS_obt_B102, LS_obt_B103, LS_obt_L004, LS_obt_L007, LS_obt_L008, LS_obt_L009, LS_obt_L013, LS_obt_L016, LS_obt_L282, LS_obt_L283, LS_obt_L547, LS_obt_L548 #####MOTU_11##### LS_obt_L084 #####MOTU_12##### LS_piv_B060, LS_piv_B076, LS_piv_B078, LS_piv_B093, LS_piv_B094, LS_piv_B095, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099, LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144, LS_piv_L002, LS_piv_L003, LS_piv_L005, LS_piv_L006, LS_piv_L010, LS_piv_L011, LS_piv_L014, LS_piv_L284, LS_piv_L371 #####MOTU_13##### LS_rei_B072, LS_rei_B073, LS_rei_L338, LS_rei_L339, LS_rei_L341, LS_rei_L342, LS_rei_L343, LS_rei_L353, LS_rei_L355, LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779 #####MOTU_14##### LS_tri_L179, LS_tri_L180, LS_tri_L182 #####MOTU_15##### LS_tri_L519, LS_tri_L618, LS_tri_L621, LS_tri_L690, LS_tri_L955 #####MOTU_16##### LS_mac_B082, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L212, LS_mac_L225, LS_mac_L290, LS_mac_L890, LS_mac_L891 Using k2p distance
In [14]:
ABGD.print_summary()
Out[14]:
| Mean | Max | NN | DtoNN | |
|---|---|---|---|---|
| MOTU_01 | 0.000000 | 0.00000 | MOTU_10 | 6.77516 |
| MOTU_02 | 0.000000 | 0.00000 | MOTU_03 | 3.98825 |
| MOTU_03 | 0.000000 | 0.00000 | MOTU_02 | 3.98825 |
| MOTU_04 | 0.037100 | 0.16695 | MOTU_09 | 2.73593 |
| MOTU_05 | 0.000000 | 0.00000 | MOTU_10 | 7.68126 |
| MOTU_06 | 0.136404 | 0.34101 | MOTU_16 | 1.55005 |
| MOTU_07 | NaN | NaN | MOTU_15 | 7.47916 |
| MOTU_08 | 0.000000 | 0.00000 | MOTU_01 | 11.60407 |
| MOTU_09 | 0.000000 | 0.00000 | MOTU_04 | 2.73593 |
| MOTU_10 | 0.143081 | 0.50167 | MOTU_09 | 2.84291 |
| MOTU_11 | NaN | NaN | MOTU_12 | 2.90372 |
| MOTU_12 | 0.266286 | 1.00758 | MOTU_11 | 2.90372 |
| MOTU_13 | 0.316828 | 0.70177 | MOTU_03 | 6.14484 |
| MOTU_14 | 0.000000 | 0.00000 | MOTU_15 | 6.33176 |
| MOTU_15 | 0.000000 | 0.00000 | MOTU_16 | 4.51779 |
| MOTU_16 | 0.000000 | 0.00000 | MOTU_06 | 1.55005 |
Analyzing data using ASAP species delimitation¶
In [15]:
ASAP=SPdel.run_ASAP(basepath,Inputs)
groups ASAPscores ASAP_1 24 7.5 ASAP_2 19 6.5 ASAP_3 18 4.5 ASAP_4 17 7.5 ASAP_5 16 2.0 ASAP_6 15 1.5 ASAP_7 15 9.5 ASAP_8 13 5.0 ASAP_9 12 3.5 ASAP_10 7 11.0 ##################### ASAP MOTUs ##################### #####MOTU_01##### LS_brn_L930, LS_brn_L931, LS_brn_L932 #####MOTU_02##### LS_con_L210, LS_con_L211 #####MOTU_03##### LS_con_L286, LS_con_L291, LS_con_L292, LS_con_L820 #####MOTU_04##### LS_elo_L1041, LS_elo_L1046, LS_elo_L1047, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L309, LS_elo_L287 #####MOTU_05##### LS_obt_B031, LS_obt_B070, LS_obt_B071, LS_obt_B090, LS_obt_L253, LS_obt_L266, LS_obt_L267, LS_obt_L268, LS_obt_L269, LS_obt_L314, LS_obt_L315, LS_obt_L316, LS_obt_L320 #####MOTU_06##### LS_obt_B074, LS_obt_B075, LS_obt_B077, LS_obt_L004, LS_obt_L007, LS_obt_L009, LS_obt_L013, LS_obt_L016, LS_obt_L282, LS_obt_L283, LS_obt_L547, LS_obt_L548, LS_obt_L008, LS_obt_B100, LS_obt_B101, LS_obt_B102, LS_obt_B103 #####MOTU_07##### LS_obt_L084 #####MOTU_08##### LS_piv_B060, LS_piv_B076, LS_piv_B078, LS_piv_B093, LS_piv_B094, LS_piv_B095, LS_piv_L002, LS_piv_L003, LS_piv_L005, LS_piv_L006, LS_piv_L010, LS_piv_L011, LS_piv_L014, LS_piv_L284, LS_piv_L371, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099, LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144 #####MOTU_09##### LS_rei_B072, LS_rei_B073, LS_rei_L338, LS_rei_L339, LS_rei_L341, LS_rei_L342, LS_rei_L343, LS_rei_L353, LS_rei_L355, LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779 #####MOTU_10##### LS_gar_L293, LS_gar_L294, LS_gar_L295, LS_gar_L296, LS_gar_L298 #####MOTU_11##### LS_mac_B061, LS_mac_B086, LS_mac_B087, LS_mac_B088, LS_mac_B089, LS_mac_B082, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L212, LS_mac_L225, LS_mac_L290, LS_mac_L890, LS_mac_L891 #####MOTU_12##### LS_tri_L519, LS_tri_L618, LS_tri_L621, LS_tri_L690, LS_tri_L955 #####MOTU_13##### LS_tri_L179, LS_tri_L180, LS_tri_L182 #####MOTU_14##### LS_muy_L907 #####MOTU_15##### LS_muy_L913, LS_muy_L914, LS_muy_L915 Using k2p distance
In [16]:
ASAP.print_summary()
Out[16]:
| Mean | Max | NN | DtoNN | |
|---|---|---|---|---|
| MOTU_01 | 0.000000 | 0.00000 | MOTU_06 | 6.77516 |
| MOTU_02 | 0.000000 | 0.00000 | MOTU_03 | 3.98825 |
| MOTU_03 | 0.000000 | 0.00000 | MOTU_02 | 3.98825 |
| MOTU_04 | 0.037100 | 0.16695 | MOTU_05 | 2.73593 |
| MOTU_05 | 0.000000 | 0.00000 | MOTU_04 | 2.73593 |
| MOTU_06 | 0.143081 | 0.50167 | MOTU_05 | 2.84291 |
| MOTU_07 | NaN | NaN | MOTU_08 | 2.90372 |
| MOTU_08 | 0.266286 | 1.00758 | MOTU_07 | 2.90372 |
| MOTU_09 | 0.316828 | 0.70177 | MOTU_03 | 6.14484 |
| MOTU_10 | 0.000000 | 0.00000 | MOTU_06 | 7.68126 |
| MOTU_11 | 0.903538 | 1.85854 | MOTU_12 | 4.51779 |
| MOTU_12 | 0.000000 | 0.00000 | MOTU_11 | 4.51779 |
| MOTU_13 | 0.000000 | 0.00000 | MOTU_12 | 6.33176 |
| MOTU_14 | NaN | NaN | MOTU_12 | 7.47916 |
| MOTU_15 | 0.000000 | 0.00000 | MOTU_01 | 11.60407 |
Analyzing data using any species delimitation precalculate from a csv file¶
In [17]:
csv_file= './data/Megaleporinus/BIN_list.csv'
In [18]:
csv_motus=SPdel.run_csvList(basepath,Inputs,csv_file)
##################### BIN MOTUs ##################### #####MOTU_AAB8569##### LS_piv_B060, LS_piv_B076, LS_piv_B078, LS_piv_B093, LS_piv_B094, LS_piv_B095, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099, LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144, LS_piv_L002, LS_piv_L003, LS_piv_L005, LS_piv_L006, LS_piv_L010, LS_piv_L011, LS_piv_L014, LS_piv_L284, LS_piv_L371 #####MOTU_AAB8578##### LS_obt_B074, LS_obt_B075, LS_obt_B077, LS_obt_B100, LS_obt_B101, LS_obt_B102, LS_obt_B103, LS_obt_L004, LS_obt_L007, LS_obt_L008, LS_obt_L009, LS_obt_L013, LS_obt_L016, LS_obt_L282, LS_obt_L283, LS_obt_L547, LS_obt_L548 #####MOTU_AAD1729##### LS_rei_B072, LS_rei_B073, LS_rei_L338, LS_rei_L339, LS_rei_L341, LS_rei_L342, LS_rei_L343, LS_rei_L353, LS_rei_L355, LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779 #####MOTU_AAE5328##### LS_mac_B082, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L212, LS_mac_L225, LS_mac_L290, LS_mac_L890, LS_mac_L891 #####MOTU_ABY2894##### LS_elo_L1041, LS_elo_L1046, LS_elo_L1047, LS_elo_L287, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L309 #####MOTU_ABZ0928##### LS_obt_B031, LS_obt_B070, LS_obt_B071, LS_obt_B090, LS_obt_L253, LS_obt_L266, LS_obt_L267, LS_obt_L268, LS_obt_L269, LS_obt_L314, LS_obt_L315, LS_obt_L316, LS_obt_L320 #####MOTU_ACL3073##### LS_tri_L519, LS_tri_L618, LS_tri_L621, LS_tri_L690, LS_tri_L955 #####MOTU_ACL3074##### LS_tri_L179, LS_tri_L180, LS_tri_L182 #####MOTU_ACL3227##### LS_gar_L293, LS_gar_L294, LS_gar_L295, LS_gar_L296, LS_gar_L298 #####MOTU_ACL3731##### LS_con_L210, LS_con_L211 #####MOTU_ACL3942##### LS_obt_L084 #####MOTU_ACL4264##### LS_con_L286, LS_con_L291, LS_con_L292, LS_con_L820 #####MOTU_ACO1303##### LS_mac_B061, LS_mac_B086, LS_mac_B087, LS_mac_B088, LS_mac_B089 #####MOTU_ADB0463##### LS_brn_L930, LS_brn_L931, LS_brn_L932 #####MOTU_ADB0512##### LS_muy_L907 #####MOTU_ADB0701##### LS_muy_L913, LS_muy_L914, LS_muy_L915 Using k2p distance
In [19]:
csv_motus['BIN'].print_summary()
Out[19]:
| Mean | Max | NN | DtoNN | |
|---|---|---|---|---|
| MOTU_AAB8569 | 0.266286 | 1.00758 | MOTU_ACL3942 | 2.90372 |
| MOTU_AAB8578 | 0.143081 | 0.50167 | MOTU_ABZ0928 | 2.84291 |
| MOTU_AAD1729 | 0.316828 | 0.70177 | MOTU_ACL4264 | 6.14484 |
| MOTU_AAE5328 | 0.000000 | 0.00000 | MOTU_ACO1303 | 1.55005 |
| MOTU_ABY2894 | 0.037100 | 0.16695 | MOTU_ABZ0928 | 2.73593 |
| MOTU_ABZ0928 | 0.000000 | 0.00000 | MOTU_ABY2894 | 2.73593 |
| MOTU_ACL3073 | 0.000000 | 0.00000 | MOTU_AAE5328 | 4.51779 |
| MOTU_ACL3074 | 0.000000 | 0.00000 | MOTU_ACL3073 | 6.33176 |
| MOTU_ACL3227 | 0.000000 | 0.00000 | MOTU_AAB8578 | 7.68126 |
| MOTU_ACL3731 | 0.000000 | 0.00000 | MOTU_ACL4264 | 3.98825 |
| MOTU_ACL3942 | NaN | NaN | MOTU_AAB8569 | 2.90372 |
| MOTU_ACL4264 | 0.000000 | 0.00000 | MOTU_ACL3731 | 3.98825 |
| MOTU_ACO1303 | 0.136404 | 0.34101 | MOTU_AAE5328 | 1.55005 |
| MOTU_ADB0463 | 0.000000 | 0.00000 | MOTU_AAB8578 | 6.77516 |
| MOTU_ADB0512 | NaN | NaN | MOTU_ACL3073 | 7.47916 |
| MOTU_ADB0701 | 0.000000 | 0.00000 | MOTU_ADB0463 | 11.60407 |
Comparing the different species delimitation results¶
In [20]:
Compare_list = 'All'
In [21]:
compared=SPdel.run_comparison(basepath,Inputs,Compare_list)
##################### Consensus MOTUs ##################### ### MOTU totally matching the taxonomy ### Consensus MOTU 01 [LS_brn_(Nominal)&MOTU_01_(ABGD)&MOTU_01_(ASAP)&MOTU_ADB0463_(BIN)&MOTU_03_(bPTP)&MOTU_15_(GMYC)&MOTU_03_(mPTP)&MOTU_03_(PTP)] LS_brn_L930, LS_brn_L931, LS_brn_L932 Consensus MOTU 02 [LS_elo_(Nominal)&MOTU_04_(ABGD)&MOTU_04_(ASAP)&MOTU_ABY2894_(BIN)&MOTU_10_(bPTP)&MOTU_06_(GMYC)&MOTU_04_(mPTP)&MOTU_10_(PTP)] LS_elo_L1041, LS_elo_L1046, LS_elo_L1047, LS_elo_L287, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L309 Consensus MOTU 03 [LS_gar_(Nominal)&MOTU_05_(ABGD)&MOTU_10_(ASAP)&MOTU_ACL3227_(BIN)&MOTU_04_(bPTP)&MOTU_09_(GMYC)&MOTU_09_(mPTP)&MOTU_04_(PTP)] LS_gar_L293, LS_gar_L294, LS_gar_L295, LS_gar_L296, LS_gar_L298 ### MOTU mostly matching the taxonomy ### Consensus MOTU 04 [LS_piv_(Nominal)&MOTU_12_(ABGD)&MOTU_08_(ASAP)&MOTU_AAB8569_(BIN)&MOTU_07_(mPTP)] LS_piv_B060, LS_piv_B076, LS_piv_B078, LS_piv_B093, LS_piv_B094, LS_piv_B095, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099, LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144, LS_piv_L002, LS_piv_L003, LS_piv_L005, LS_piv_L006, LS_piv_L010, LS_piv_L011, LS_piv_L014, LS_piv_L284, LS_piv_L371 ### MOTU totally mismatching the taxonomy ### Consensus MOTU 05 [MOTU_02_(ABGD)&MOTU_02_(ASAP)&MOTU_ACL3731_(BIN)&MOTU_07_(bPTP)&MOTU_16_(GMYC)&MOTU_02_(mPTP)&MOTU_07_(PTP)] LS_con_L210, LS_con_L211 Consensus MOTU 06 [MOTU_03_(ABGD)&MOTU_03_(ASAP)&MOTU_ACL4264_(BIN)&MOTU_06_(bPTP)&MOTU_11_(GMYC)&MOTU_01_(mPTP)&MOTU_06_(PTP)] LS_con_L286, LS_con_L291, LS_con_L292, LS_con_L820 Consensus MOTU 07 [MOTU_07_(ABGD)&MOTU_14_(ASAP)&MOTU_ADB0512_(BIN)&MOTU_02_(bPTP)&MOTU_18_(GMYC)&MOTU_13_(mPTP)&MOTU_02_(PTP)] LS_muy_L907 Consensus MOTU 08 [MOTU_08_(ABGD)&MOTU_15_(ASAP)&MOTU_ADB0701_(BIN)&MOTU_01_(bPTP)&MOTU_14_(GMYC)&MOTU_12_(mPTP)&MOTU_01_(PTP)] LS_muy_L913, LS_muy_L914, LS_muy_L915 Consensus MOTU 09 [MOTU_09_(ABGD)&MOTU_05_(ASAP)&MOTU_ABZ0928_(BIN)&MOTU_11_(bPTP)&MOTU_04_(GMYC)&MOTU_05_(mPTP)&MOTU_11_(PTP)] LS_obt_B031, LS_obt_B070, LS_obt_B071, LS_obt_B090, LS_obt_L253, LS_obt_L266, LS_obt_L267, LS_obt_L268, LS_obt_L269, LS_obt_L314, LS_obt_L315, LS_obt_L316, LS_obt_L320 Consensus MOTU 10 [MOTU_10_(ABGD)&MOTU_06_(ASAP)&MOTU_AAB8578_(BIN)&MOTU_09_(bPTP)&MOTU_01_(GMYC)&MOTU_06_(mPTP)&MOTU_09_(PTP)] LS_obt_B074, LS_obt_B075, LS_obt_B077, LS_obt_B100, LS_obt_B101, LS_obt_B102, LS_obt_B103, LS_obt_L004, LS_obt_L007, LS_obt_L008, LS_obt_L009, LS_obt_L013, LS_obt_L016, LS_obt_L282, LS_obt_L283, LS_obt_L547, LS_obt_L548 Consensus MOTU 11 [MOTU_11_(ABGD)&MOTU_07_(ASAP)&MOTU_ACL3942_(BIN)&MOTU_12_(bPTP)&MOTU_17_(GMYC)&MOTU_08_(mPTP)&MOTU_12_(PTP)] LS_obt_L084 Consensus MOTU 12 [MOTU_14_(ABGD)&MOTU_13_(ASAP)&MOTU_ACL3074_(BIN)&MOTU_05_(bPTP)&MOTU_13_(GMYC)&MOTU_14_(mPTP)&MOTU_05_(PTP)] LS_tri_L179, LS_tri_L180, LS_tri_L182 Consensus MOTU 13 [MOTU_15_(ABGD)&MOTU_12_(ASAP)&MOTU_ACL3073_(BIN)&MOTU_08_(bPTP)&MOTU_08_(GMYC)&MOTU_17_(mPTP)&MOTU_08_(PTP)] LS_tri_L519, LS_tri_L618, LS_tri_L621, LS_tri_L690, LS_tri_L955 ### MOTUs mostly mismatching the taxonomy ### Consensus MOTU 14 [MOTU_06_(ABGD)&MOTU_ACO1303_(BIN)&MOTU_13_(bPTP)&MOTU_05_(GMYC)&MOTU_15_(mPTP)&MOTU_13_(PTP)] LS_mac_B061, LS_mac_B086, LS_mac_B087, LS_mac_B088, LS_mac_B089 Consensus MOTU 15 [MOTU_16_(ABGD)&MOTU_AAE5328_(BIN)&MOTU_14_(bPTP)&MOTU_03_(GMYC)&MOTU_16_(mPTP)&MOTU_14_(PTP)] LS_mac_B082, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L212, LS_mac_L225, LS_mac_L290, LS_mac_L890, LS_mac_L891 Consensus MOTU 16 [MOTU_15_(bPTP)&MOTU_12_(GMYC)&MOTU_10_(mPTP)&MOTU_15_(PTP)] LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779 Consensus MOTU 17 [MOTU_16_(bPTP)&MOTU_07_(GMYC)&MOTU_11_(mPTP)&MOTU_16_(PTP)] LS_rei_B072, LS_rei_L342, LS_rei_B073, LS_rei_L341, LS_rei_L338, LS_rei_L355, LS_rei_L339, LS_rei_L343, LS_rei_L353 Using k2p distance
In [22]:
SPdel.plot_compare_tree(basepath, Inputs.tree, compared[0])
##### Warning: Nominal species not contigous in the tree. #####
Saving tree plot as svg
In [23]:
SPdel.plot_compare_tree(basepath, Inputs.tree, compared[0],save=True)
##### Warning: Nominal species not contigous in the tree. #####
In [24]:
compared[1].print_summary()
Out[24]:
| Mean | Max | NN | DtoNN | |
|---|---|---|---|---|
| MOTU_01 | 0.000000 | 0.00000 | MOTU_10 | 6.77516 |
| MOTU_02 | 0.037100 | 0.16695 | MOTU_09 | 2.73593 |
| MOTU_03 | 0.000000 | 0.00000 | MOTU_10 | 7.68126 |
| MOTU_04 | 0.266286 | 1.00758 | MOTU_11 | 2.90372 |
| MOTU_05 | 0.000000 | 0.00000 | MOTU_06 | 3.98825 |
| MOTU_06 | 0.000000 | 0.00000 | MOTU_05 | 3.98825 |
| MOTU_07 | NaN | NaN | MOTU_13 | 7.47916 |
| MOTU_08 | 0.000000 | 0.00000 | MOTU_01 | 11.60407 |
| MOTU_09 | 0.000000 | 0.00000 | MOTU_02 | 2.73593 |
| MOTU_10 | 0.143081 | 0.50167 | MOTU_09 | 2.84291 |
| MOTU_11 | NaN | NaN | MOTU_04 | 2.90372 |
| MOTU_12 | 0.000000 | 0.00000 | MOTU_13 | 6.33176 |
| MOTU_13 | 0.000000 | 0.00000 | MOTU_15 | 4.51779 |
| MOTU_14 | 0.136404 | 0.34101 | MOTU_15 | 1.55005 |
| MOTU_15 | 0.000000 | 0.00000 | MOTU_14 | 1.55005 |
| MOTU_16 | 0.000000 | 0.00000 | MOTU_17 | 0.67115 |
| MOTU_17 | 0.000000 | 0.00000 | MOTU_16 | 0.67115 |
In [25]:
compared[1].plot_max_min()
In [26]:
compared[1].plot_freq()
In [27]:
compared[1].plot_heatmap(upper=4)
Thanks for use SPdel!